{"id":"W6939027159","doi":"10.6068/dp14ba8afaf2413","title":"Trend 1961 - 2013. Statistics Canada. CANSIM: Construction - Machinery and Equipment | Country: Canada | Table: Flows and stocks of fixed non-residential capital, by sector of North American Industry Classification System (NAICS) and asset | Variable: Hyperbolic (delayed) end-year net stock, Marine engineering (x 1,000,000), Business sector, | Units: $CAD Chained (2007) $CAD, 1961-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-034.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Census; Official statistics; Summary statistics; Index (typography); Stock (firearms); Descriptive statistics; Publication; Business statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002384461,0.0005024027,0.0008183157,0.00006249785,0.0001173675,0.0001226165,0.0005251021,0.0003182123,0.00169283],"category_scores_gemma":[0.00006413383,0.0003241594,3.625434e-7,0.0003618614,0.00008880049,0.0001757786,0.0003186319,0.0005993817,0.000002048667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001042455,"about_ca_system_score_gemma":0.0009684075,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9995158,"about_ca_topic_score_gemma":0.995983,"domain_scores_codex":[0.9973944,0.0001795789,0.000706808,0.0007138366,0.0005738215,0.0004315977],"domain_scores_gemma":[0.9975035,0.0007945994,0.0007341597,0.0004617909,0.0001156996,0.0003902992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001181781,0.00003459396,0.001553562,0.0004610361,0.0001989326,0.00002901451,0.000001852719,0.00004569658,0.0003047548,0.0000520913,0.9968475,0.000352814],"study_design_scores_gemma":[0.0002509214,0.0001310159,0.0007257854,0.00006585485,0.0002542021,0.0002117066,0.0002001613,0.01170694,2.247243e-7,3.348385e-8,0.9859822,0.0004709007],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001683695,0.0005886689,0.000007844576,0.00000416347,0.0006489383,0.0005608108,0.9962825,0.00003850496,0.0001849041],"genre_scores_gemma":[0.003244278,0.001412514,0.0001032071,0.00002694272,0.0002748305,0.00001875219,0.9946754,0.0000256801,0.0002184052],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01166124,"threshold_uncertainty_score":0.999921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01287499912817918,"score_gpt":0.2001563258994214,"score_spread":0.1872813267712422,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}